[1] The combination of glacier outlines with digital elevation models (DEMs) opens new dimensions for research on climate change impacts over entire mountain chains. Of particular interest is the modeling of glacier thickness distribution, where several new approaches were proposed recently. The tool applied herein, GlabTop (Glacier bed Topography) is a fast and robust approach to model thickness distribution and bed topography for large glacier samples using a Geographic Information System (GIS). The method is based on an empirical relation between average basal shear stress and elevation range of individual glaciers, calibrated with geometric information from paleoglaciers, and validated with radio echo soundings on contemporary glaciers. It represents an alternative and independent test possibility for approaches based on mass-conservation and flow. As an example for using GlabTop in entire mountain ranges, we here present the modeled ice thickness distribution and bed topography for all Swiss glaciers along with a geomorphometric analysis of glacier characteristics and the overdeepenings found in the modeled glacier bed. These overdeepenings can be seen as potential sites for future lake formation and are thus highly relevant in connection with hydropower production and natural hazards. The thickest ice of the largest glaciers rests on weakly inclined bedrock at comparably low elevations, resulting in a limited potential for a terminus retreat to higher elevations. The calculated total glacier volume for all Swiss glaciers is 75 AE 22 km 3 for 1973 and 65 AE 20 km 3 in 1999. Considering an uncertainty range of AE30%, these results are in good agreement with estimates from other approaches.Citation: Linsbauer, A., F. Paul, and W. Haeberli (2012), Modeling glacier thickness distribution and bed topography over entire mountain ranges with GlabTop: Application of a fast and robust approach,
Abstract. Ice volume estimates are crucial for assessing water reserves stored in glaciers. Due to its large glacier coverage, such estimates are of particular interest for the Himalayan-Karakoram (HK) region. In this study, different existing methodologies are used to estimate the ice reserves: three area-volume relations, one slope-dependent volume estimation method, and two ice-thickness distribution models are applied to a recent, detailed, and complete glacier inventory of the HK region, spanning over the period [2000][2001][2002][2003][2004][2005][2006][2007][2008][2009][2010] and revealing an ice coverage of 40 775 km 2 . An uncertainty and sensitivity assessment is performed to investigate the influence of the observed glacier area and important model parameters on the resulting total ice volume. Results of the two ice-thickness distribution models are validated with local icethickness measurements at six glaciers. The resulting ice volumes for the entire HK region range from 2955 to 4737 km 3 , depending on the approach. This range is lower than most previous estimates. Results from the ice thickness distribution models and the slope-dependent thickness estimations agree well with measured local ice thicknesses. However, total volume estimates from area-related relations are larger than those from other approaches. The study provides evidence on the significant effect of the selected method on results and underlines the importance of a careful and critical evaluation.
Abstract. Knowledge of the ice thickness distribution of glaciers and ice caps is an important prerequisite for many glaciological and hydrological investigations. A wealth of approaches has recently been presented for inferring ice thickness from characteristics of the surface. With the Ice Thickness Models Intercomparison eXperiment (ITMIX) we performed the first coordinated assessment quantifying individual model performance. A set of 17 different models showed that individual ice thickness estimates can differ considerably – locally by a spread comparable to the observed thickness. Averaging the results of multiple models, however, significantly improved the results: on average over the 21 considered test cases, comparison against direct ice thickness measurements revealed deviations on the order of 10 ± 24 % of the mean ice thickness (1σ estimate). Models relying on multiple data sets – such as surface ice velocity fields, surface mass balance, or rates of ice thickness change – showed high sensitivity to input data quality. Together with the requirement of being able to handle large regions in an automated fashion, the capacity of better accounting for uncertainties in the input data will be a key for an improved next generation of ice thickness estimation approaches.
ABSTRACT. Surface digital elevation models (DEMs) and slope-related estimates of glacier thickness enable modelling of glacier-bed topographies over large ice-covered areas. Due to the erosive power of glaciers, such bed topographies can contain numerous overdeepenings, which when exposed following glacier retreat may fill with water and form new lakes. In this study, the bed overdeepenings for �28 000 glaciers (40 775
Abstract. In the course of glacier retreat, new glacier lakes can develop. As such lakes can be a source of natural hazards, strategies for predicting future glacier lake formation are important for an early planning of safety measures. In this article, a multi-level strategy for the identification of overdeepened parts of the glacier beds and, hence, sites with potential future lake formation, is presented. At the first two of the four levels of this strategy, glacier bed overdeepenings are estimated qualitatively and over large regions based on a digital elevation model (DEM) and digital glacier outlines. On level 3, more detailed and laborious models are applied for modeling the glacier bed topography over smaller regions; and on level 4, special situations must be investigated in-situ with detailed measurements such as geophysical soundings. The approaches of the strategy are validated using historical data from Trift Glacier, where a lake formed over the past decade. Scenarios of future glacier lakes are shown for the two test regions Aletsch and Bernina in the Swiss Alps. In the Bernina region, potential future lake outbursts are modeled, using a GIS-based hydrological flow routing model. As shown by a corresponding test, the ASTER GDEM and the SRTM DEM are both suitable to be used within the proposed strategy. Application of this strategy in other mountain regions of the world is therefore possible as well.
A re-analysis is presented here of a 10 year mass balance series at Findelengletscher, a temperate mountain glacier in Switzerland. Calculating glacier-wide mass balance from the set of glaciological point balance observations using conventional approaches, such as the profile or contour method, resulted in significant deviations from the reference value given by the geodetic mass change over a 5 year period. This is attributed to the sparsity of observations at high elevations and to the inability of the evaluation schemes to adequately estimate accumulation in unmeasured areas. However, measurements of winter mass balance were available for large parts of the study period from snow probings and density pits. Complementary surveys by helicopter-borne ground-penetrating radar (GPR) were conducted in three consecutive years. The complete set of seasonal observations was assimilated using a distributed mass balance model. This model-based extrapolation revealed a substantial mass loss at Findelengletscher of −0.43 m w.e. a −1 between 2004 and 2014, while the loss was less pronounced for its former tributary, Adlergletscher (−0.30 m w.e. a −1 ). For both glaciers, the resulting time series were within the uncertainty bounds of the geodetic mass change. We show that the model benefited strongly from the ability to integrate seasonal observations. If no winter mass balance measurements were available and snow cover was represented by a linear precipitation gradient, the geodetic mass balance was not matched. If winter balance measurements by snow probings and snow density pits were taken into account, the model performance was substantially improved but still showed a significant bias relative to the geodetic mass change. Thus, the excellent agreement of the model-based extrapolation with the geodetic mass change was owed to an adequate representation of winter accumulation distribution by means of extensive GPR measurements.
Glacial lake outburst floods (GLOFs) are a serious and potentially increasing threat to livelihoods and infrastructure in most high-mountain regions of the world. Here, we integrate modelling approaches that capture both current and future potential for GLOF triggering, quantification of affected downstream areas, and assessment of the underlying societal vulnerability to such climate-related disasters, to implement a first-order assessment of GLOF risk across the Himalayan state of Himachal Pradesh (HP), Northern India. The assessment thereby considers both current glacial lakes and modelled future lakes that are expected to form as glaciers retreat. Current hazard, vulnerability, and exposure indices are combined to reveal several risk 'hotspots', illustrating that significant GLOF risk may in some instances occur far downstream from the glaciated headwaters where the threats originate. In particular, trans-national GLOFs originating in the upper Satluj River Basin (China) are a threat to downstream areas of eastern HP. For the future deglaciated scenario, a significant increase in GLOF hazard levels is projected across most administrative units, as lakes expand or form closer towards steep headwalls from which impacts of falling ice and rock may trigger outburst events. For example, in the central area of Kullu, a 7-fold increase in the probability of GLOF triggering and a 3-fold increase in the downstream area affected by potential GLOF paths can be anticipated, leading to an overall increase in the assigned GLOF hazard level from 'high' to 'very high'. In such instances, strengthening resilience and capacities to reduce the current GLOF risk will provide an important first step towards adapting to future challenges.
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